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Assessment of the efficacy of total lymphocyte counts as predictors of AIDS defining infections in HIV-1 infected people

St Stephen’s Centre, Chelsea and Westminster Hospital, London, UK

Correspondence to:
Correspondence to:
Dr J Stebbing
Department of Immunology, Chelsea and Westminster Hospital, 369 Fulham Road, London SW10 9NH, UK; j.stebbing{at}imperial.ac.uk

Background: The CD4 count is a dominant prognostic and predictive factor in HIV infection. This study assessed the utility of the total lymphocyte count (TLC) in place of the CD4 count to predict the development of AIDS defining opportunistic infections (ADOI).

Methods: The Chelsea and Westminster cohort was used to identify those people with a first episode of an ADOI. Corresponding CD4 and TLCs were recorded before diagnosis or at the time of first prescribing prophylaxis; patients without an AIDS defining opportunistic infection were defined as being at "risk" and receiver operating characteristic (ROC) curves were used to display the results of sensitivity and the false positive error rate of total lymphocyte and CD4 count groups.

Results: A significant linear correlation was seen between the log₁₀ CD4 count and log₁₀ TLC (Pearson’s correlation coefficient = 0.70, p<0.001). The finer cut off value for TLC where false positive error rate is minimum and sensitivity maximum was 1500–2000 cells/mm³. Patients with TLC 1000–1500 cells/mm³ were estimated to be at 40% increased risk of developing an ADOI. The cut off value for CD4 counts measured 200 cells/mm³ above which the risk developing an ADOI decreased. Patients with a CD4 count of 150–200 cells/mm³ were at a 34% increased risk of developing an ADOI. The area under the ROC curve for TLC was 10% lower than that for CD4 count.

Conclusions: The TLC is minimally less reliable than the CD4 count as a predictor of ADOIs. In the absence of expensive equipment for CD4 measurement, the TLC is a useful test.

Abbreviations: TLC, total lymphocyte count; ADOI, AIDS defining opportunistic infections; ROC, receiver operator curve

Keywords: lymphocyte count; CD4; opportunistic infection; receiver operating characteristic curve

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